The self-learning AI that maps and anticipates malicious behavior patterns.
The core intelligence of VeilNet AI is its Threat Graph — a continuously updating knowledge engine that maps processes, transactions, and behaviors across time.
Unlike static defense systems, the Threat Graph:
Models Relationships: Every action, from a file write to a contract approval, is analyzed in the context of related behaviors. Suspicious clusters are flagged even if individual actions seem normal.
Learns From Every Attack: Each new threat enriches the dataset, enabling faster and more accurate detection for all users.
Predicts Future Risks: By observing patterns, it can anticipate when an ongoing process may evolve into an attack. For example, if a process accesses wallet data and simultaneously requests external connections, it is escalated immediately.
Global & Local Feedback Loops: While each user’s Threat Graph operates locally for privacy, anonymized insights can be aggregated (opt-in only) to improve the global AI defense layer.
This creates an ever-evolving shield where VeilNet AI doesn’t just react to today’s threats but anticipates tomorrow’s attacks, continuously adapting to new malware strains, phishing techniques, and Web3 exploits.